Who conducts biological research, where, and how the results are disseminated varies among geographies and identities. Identifying and documenting these forms of bias by research communities is a critical first step towards addressing them. We documented perceived and observed biases in movement ecology. Movement ecology is a rapidly expanding sub-discipline of biology, which is strongly underpinned by fieldwork and technology use. First, we surveyed attendees of an international conference, and discussed the results at the conference (comparing uninformed vs informed perceived bias). Although most researchers identified as bias-aware, only a subset of biases were discussed in conversation. Next, by considering author affiliations from publications in the journal Movement Ecology, we found among-country discrepancies between the country of the authors’ affiliation and study site location related to national economics. At the within-country scale, we found that race-gender identities of postgraduate biology researchers in the USA differed from national demographics. We discuss the role of potential specific causes for the emergence of bias in the sub-discipline, e.g. parachute-science or accessibility to fieldwork. Undertaking data-driven analysis of bias within research sub-disciplines can help identify specific barriers and first steps towards the inclusion of a greater diversity of participants in the scientific process.

Placing wind turbines within large migration flyways, such as the North Sea basin, can contribute to the decline of vulnerable migratory bird populations by increasing mortality through collisions. Curtailment of wind turbines limited to short periods with intense migration can minimize these negative impacts, and near‐term bird migration forecasts can inform such decisions. Although near‐term forecasts are usually created with long‐term datasets, the pace of environmental alteration due to wind energy calls for the urgent development of conservation measures that rely on existing data, even when it does not have long temporal coverage. Here, we use 5 years of tracking bird radar data collected off the western Dutch coast, weather and phenological variables to develop seasonal near‐term forecasts of low‐altitude nocturnal bird migration over the southern North Sea. Overall, the models explained 71% of the variance and correctly predicted migration intensity above or below a threshold for intense hourly migration in more than 80% of hours in both seasons. However, the percentage of correctly predicted intense migration hours (top 5% of hours with the most intense migration) was low, likely due to the short‐term dataset and their rare occurrence. We, therefore, advise careful consideration of a curtailment threshold to achieve optimal results. Synthesis and applications: Near‐term forecasts of migration fluxes evaluated against measurements can be used to define curtailment thresholds for offshore wind energy. We show that to minimize collision risk for 50% of migrants, if predicted correctly, curtailments should be applied during 18 h in spring and 26 in autumn in the focal year of model assessments, resulting in an estimated annual wind energy loss of 0.12%. Drawing from the Dutch curtailment framework, which pioneered the ‘international first’ offshore curtailment, we argue that using forecasts developed from limited temporal datasets alongside expert insight and data‐driven policies can expedite conservation efforts in a rapidly changing world. This approach is particularly valuable in light of increasing interannual variability in weather conditions.

Each year, millions of birds migrate nocturnally over the North Sea basin, an area designated for significant offshore wind energy development. Wind turbines can harm aerial wildlife through collisions and barrier effects, especially when birds fly at low altitudes below the wind turbine rotor tip. We aim to quantify seasonal and nightly differences in flight altitudes of nocturnal bird migration over the North Sea and identify how weather influences low‐altitude flight to inform wind turbine curtailment procedures for reducing bird fatalities. We used bird tracking radars at Borssele and Luchterduinen offshore wind parks, 22 and 23 km from the western Dutch coast, to monitor altitude distributions during migration. We show that median flight altitude was higher in spring compared to autumn at Borssele (spring: 285.5 m, autumn: 169.2 m; p < .001, effect size [ES] = 0.0001) and Luchterduinen (spring: 133.8 m, autumn: 126.0 m; p < .001, ES = 0.002) and below wind turbine rotor tip in both seasons. On most nights in both seasons, the majority of migrants flew predominantly at low altitudes, except for intense migration nights in spring in Borssele where, on 87% of these nights, migration mainly occurred at high altitudes. The most important predictors of low‐altitude migration in both seasons were day of year and wind assistance. Birds chose altitudes with the most favorable wind conditions for migration in both seasons. The relationship between day of year and low‐altitude migration fraction suggests that different species migrate at different altitudes. In spring, birds were flying lower at the beginning and the end of the night, reflecting departures and arrivals of birds, while radar location in autumn was a good predictor of low‐altitude flights, indicating that different local migratory axes have distinct altitude distributions. Our findings suggest that mitigation measures offshore may be more effective during autumn than spring, especially on nights with more supportive wind conditions at altitudes below 300 m.

Radar is an effective tool for continuous monitoring and quantification of aerial bird movement and used to study migration and local flight behaviour. However, systems with automated tracking algorithms do not provide the level of processing sufficient to guarantee reliable data. Therefore, post‐processing such radar data is required but often non‐trivial, especially in challenging environments such as open sea. We present a post‐processing framework that implements knowledge of the radar system and bird biology to filter the data and retrieve reliable, high‐quality tracking data. The framework is split into three modules, each with a specific aim: (I) sub‐setting based on prior knowledge of the radar system and bird flight, (II) improving bird track quality and (III) detecting and removing spatio‐temporal sections of data that have a clear bias for false observations. The effectiveness of the framework is demonstrated with a case study comparing track densities inside and outside an offshore wind farm, and by applying the workflow to a dataset of visually validated radar tracks. Application of Module I resulted in a dataset of 520.894 bird tracks (19.5% of total data) within a 10.4 km2 area. Additionally, 18.734 tracks were corrected for geometric errors in Module II, and Module III identified 236 of 719 observation hours and an area of 1.55 km2 as unreliable for spatio‐temporal analysis. No difference in track densities was found between the area inside and outside the wind farm when using the post‐processed data, whereas using the unprocessed bird tracks, lower track densities were observed outside the wind farm. Of the visually validated radar tracks, the framework removed 85% of false positive bird tracks, while retaining 80% of true positive bird tracks. The framework provides a logical workflow to increase the reliability and quality of a bird radar dataset while being adaptable to the radar system and its surroundings. This is a first step towards standardising the post‐processing methodology for automated bird radar systems, which can facilitate comparative analyses of bird movement in space and time and improve the quality of ecological impact assessments.

The southern North Sea is part of an important flyway for nocturnal bird migration, but is also risky as it stretches over a large surface of water. Selecting nights with suitable weather conditions for migration can be critical for a bird’s survival. The aim of this study is to unravel the weather-related bird migration decisions, by providing a descriptive analysis of the synoptic weather conditions over the North Sea on nights with very high and low migration intensities and compare these conditions to the prevailing climatology. For this study, bird radar data were utilized from an offshore wind farm off the Dutch coast, in the North Sea. The study suggests that atmospheric conditions clear of rain and frontal systems, dominated by high pressure systems and tailwinds in spring and sidewinds in autumn are most suitable for nights of intense migration. Differences in temperature, relative humidity and cloud cover appear less significant between intense and low migration nights, suggesting that these variables exert only a secondary role on migration. We discuss how future developments in radar aeroecology and the integration of meteorology can help improve our ability to forecast bird migration.

is why many birds exploited positive wind assistance which occurred on intense migration nights. This implies that the seasonal wind regimes over the North Sea alter its migratory dynamics which is reflected in headings, timing and intensity of migration.

Internacionalizacija marke s domaceg na inozemno tržiste jedna od strateskih odluka koje poduzece donosi i koja ima temeljan i znacajan utjecaj

Herpetological research of the Prenj and Čvrsnica mountains has a relatively long tradition, but not enough scientific attention was devoted to them. Literature data on herpetofauna of Prenj and Čvrsnica is old, sporadic and rare. The aim of this research was to collect all data on the herpetofauna for the given mountains and determine the importance of the area for the herpetofaunal biodiversity of Bosnia and Herzegovina (B-H). The analysis of data showed that the area of Prenj and Čvrsnica is inhabited by 11 species of amphibians (55 % of the total number of amphibians in B-H) and 24 species of reptiles (83% of the total number of reptiles in B-H) which differ in vertical and horizontal distribution. The registered biodiversity is extremely high and is a consequence of the geographical position of these mountains which border the Mediterranean climate zone in B-H.